class_docstr: A BlendableDataset implementation that uses less memory than the original implementation.
  Indices are computed algorithmically instead of storing them in memory.
  
  To test call: MemoryEfficientBlendableDataset.test_index_blending()
class_docstr_tok: ["A","BlendableDataset","implementation","that","uses","less","memory","than","the","original","implementation",".","Indices","are","computed","algorithmically","instead","of","storing","them","in","memory",".","To","test","call",":","MemoryEfficientBlendableDataset.test_index_blending","(",")"]
code: def __len__(self):
      return self.size
  
file_path: NeMo/nemo/collections/nlp/data/language_modeling/megatron/blendable_dataset.py
imports: import time
  import numpy
  import torch
  from nemo.utils import logging
  from nemo.utils.app_state import AppState
label_desc: Use image node_id 3 for calling the MemoryEfficientBlendableDataset obj's underlying member method code with example usage: obj.__len__() and returns: self